ArticleNMR in biomedicine2023
Integrating multimodality magnetic resonance imaging to the Allen Mouse Brain Common Coordinate Framework.
Article in NMR in biomedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A multimodal spatial atlas of transcriptomic, morphological, and electrophysiological cell type densities in the mouse brain.PLoS computational biology · 2026Article
- Decoding gray matter, large-scale analysis of brain cell morphometry to inform microstructural modeling of diffusion MR signals.Communications biology · 2026Article
- An extended and improved CCFv3 annotation and Nissl atlas of the entire mouse brain.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- High-resolution diffusion magnetic resonance imaging and spatial-transcriptomic in developing mouse brain.NeuroImage · 2024Article
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10 authors.
Funding
Abstract
High-resolution magnetic resonance imaging (MRI) affords unique image contrasts to nondestructively probe the tissue microstructure; validation of MRI findings with conventional histology is essential to better understand the MRI contrasts. However, the dramatic difference in the spatial resolution and image contrast of these two techniques impedes accurate comparison between MRI metrics and traditional histology. To better validate various MRI metrics, we acquired whole mouse brain multigradient recalled-echo and multishell diffusion MRI datasets at 25-μm isotropic resolution. The recently developed Allen Mouse Brain Common Coordinate Framework (CCFv3) provides opportunities to integrate multimodal and multiscale datasets of the whole mouse brain in a common three-dimensional (3D) space. The T2*, quantitative susceptibility mapping, diffusion tensor imaging, and neurite orientation dispersion and density imaging parameters were compared with both serial two-photon tomography images and 3D Nissl staining images in the CCFv3 at the same spatial resolution. The correlation between MRI and Nissl staining strongly depends on different metrics and different regions of the brain. Integrating different imaging modalities to the same space may substantially improve our understanding of the complexity of the brain at different scales.
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